diCal Version 1 is a scalable demographic inference method based on the sequentially Markov conditional sampling distribution framework. At present, diCal can infer a piecewise-constant population size history from the genomes of multiple individuals sampled from a single population. We are currently working on extending the method to handle more complex demography, incorporating multiple populations, population splits, migration, admixture, etc.

fastNeutrino is an efficient algorithm to infer piecewise-exponential models of the historical effective population size from the distribution of sample allele frequencies. In addition to inferring demography, our method can also accurately estimate locus-specific mutation rates.

This program computes the expected joint site frequency spectrum (SFS) for a tree-shaped demography without migration, via a multipopulation Moran model. It can handle thousands of individuals sampled from hundreds of populations related by a complex demographic model with arbitrary population size histories (including piecewise-exponential growth). It also computes the "truncated site frequency spectrum" for a single population, i.e. the frequency spectrum for mutations arising after a certain point in time. This can be used in both Moran and coalescent approaches to computing the multipopulation SFS.

Transition density functions of WF diffusion processes and their applications

Telescoper is a local assembly algorithm designed for short-reads from NGS platforms such as Illumina. The reads must come from two libraries: one short insert, and one long insert. The algorithm begins with a user-given seed string, and assembles a graph of possible extensions, and prints one path of extensions, as a fasta file.
The software is still a beta version. We have not yet tested it extensively, and envision many improvements down the line.

This program combines a recently found linear-time algorithm
for phasing genotypes on trees with a
tree-based method for association mapping. From unphased
genotype data, our algorithm builds local phylogenies along the
genome, and scores each tree according to the clustering of
cases and controls.

HapBound-GC and SHRUB-GC respectively compute lower and upper bounds on the minimum combined number of crossover and gene-conversion recombinations.
SHRUB-GC constructs a graphical representation of evolutionary history involving coalescent, mutation, crossover and gene-conversion events.